Non-operating revenue is an important source of funding for rural hospitals, especially those that are government-owned.

PURPOSE: Non-operating revenue (NOR), derived from investments, contributions, government appropriations, and medical space rentals, can contribute to financial stability of hospitals by offsetting operating losses and improving profitability. NOR might benefit rural hospitals that often face intense financial pressures. However, little is known about how much rural hospitals rely on NOR and if certain organizational characteristics are associated with differences in NOR. METHODS: Healthcare Cost Report Information System data from 2011 to 2019 were used to analyze sources of revenue among Critical Access Hospitals (CAHs) and Rural Prospective Payment System (R-PPS) hospitals through descriptive statistics and regression models. Reliance on NOR was measured by the percentage of total revenue from non-operating sources. FINDINGS: Results indicate that both CAHs and R-PPS hospitals rely on NOR; however, CAHs have a higher percentage of total revenue derived from non-operating sources (3.2%) as compared to R-PPS hospitals (1.9%) (p < 0.001). Government-owned hospitals have significantly higher reliance on NOR than other ownership types. System affiliation also influences reliance on NOR. Lastly, results suggest that NOR may play a role in improving overall profit margins. CONCLUSIONS: As rural hospitals disproportionately face challenges related to declining profitability and the risk for closure, they may rely on NOR to continue to strengthen financial performance and provide health care to their communities. However, NOR is not guaranteed, and reliance on NOR further reiterates the value of stable, adequate reimbursement to guard against fluctuations in NOR.

Uncompensated Care is Highest for Rural Hospitals, Particularly in Non-Expansion States.

High levels of uncompensated care impact hospital profitability and may create challenges for rural hospitals at financial risk of closure. We explore 2019 hospital uncompensated care as a percentage of operating expenses and draw comparisons at a state level by Medicaid expansion status and rural classification. We further compare uncompensated care in 2019 to 2014 in rural hospitals by Medicaid expansion implementation timing. We found that, overall, rural hospitals had more uncompensated care than urban hospitals in 2019 (3.81% vs. 3.12%), but there was a larger difference by expansion status (expansion states: 2.55% vs. non-expansion states: 6.28%). In all but seven states, rural hospitals reported higher uncompensated care than urban, and the 14 states with the highest uncompensated care had not expanded Medicaid. We observed that rural hospital uncompensated care in non-expansion states increased between 2014 and 2019, while the most dramatic decrease occurred in late-expansion states.

Research Note: COVID-19 Is Not an Independent Cause of Death.

The COVID-19 pandemic has had overwhelming global impacts with deleterious social, economic, and health consequences. To assess the COVID-19 death toll, researchers have estimated declines in 2020 life expectancy at birth (e0). When data are available only for COVID-19 deaths, but not for deaths from other causes, the risks of dying from COVID-19 are typically assumed to be independent of those from other causes. In this research note, we explore the soundness of this assumption using data from the United States and Brazil, the countries with the largest number of reported COVID-19 deaths. We use three methods: one estimates the difference between 2019 and 2020 life tables and therefore does not require the assumption of independence, and the other two assume independence to simulate scenarios in which COVID-19 mortality is added to 2019 death rates or is eliminated from 2020 rates. Our results reveal that COVID-19 is not independent of other causes of death. The assumption of independence can lead to either an overestimate (Brazil) or an underestimate (United States) of the decline in e0, depending on how the number of other reported causes of death changed in 2020.

COVID-19 is not an Independent Cause of Death.

The COVID-19 pandemic has had overwhelming global impacts with deleterious social, economic, and health consequences. To assess the COVID-19 death toll researchers have estimated declines in 2020 life expectancy at birth. Because data are often available only for COVID-19 deaths, the risks of dying from COVID-19 are assumed to be independent of those from other causes. We explore the soundness of this assumption based on data from the US and Brazil, the countries with the largest number of reported COVID-19 deaths. We use three methods. One estimates the difference between 2019 and 2020 life tables and therefore does not require the assumption of independence. The other two assume independence to simulate scenarios in which COVID-19 mortality is added to 2019 death rates or is eliminated from 2020 rates. Our results reveal that COVID-19 is not independent of other causes of death. The assumption of independence can lead to either an overestimate (Brazil) or an underestimate (US) of the decline in e 0 , depending on how the number of other reported causes of death changed in 2020.

Widespread pesticide contamination of drinking water and impact on cancer risk in Brazil.

Pesticides, which are associated with endocrine dysfunction, immunological dysregulation, and cancer, are widespread sources of drinking water contamination. The state of Paraná has a population of 11 million, is the second largest grain producer in Brazil and is a leading consumer of pesticides. In this study, we analyzed the extent of drinking water contamination from 11 proven, probable, or potentially carcinogenic pesticides (alachlor, aldrin-dieldrin, atrazine, chlordane, DDT-DDD-DDE, diuron, glyphosate-AMPA, lindane-γ-HCH, mancozeb-ETU, molinate, and trifluralin) in 127 grain-producing municipalities in the state of Paraná. Extensive contamination of drinking water was found, including legacy pesticides such as aldrin-dieldrin (mean 0.047 ppb), DDT-DDD-DDE (mean: 0.07), chlordane (mean: 0.181), and lindane-HCH (mean: 2.17). Most of the municipalities were significantly above the maximum limits for each one of the currently allowed pesticides (67% for alachlor, 9.44% for atrazine, 96.85% for diuron, 100% for glyphosate-AMPA, 80.31% for mancozeb-ETU, 91.33% for molinate, and 12.6% for trifluralin). Ninety-seven percent of municipalities presented a sum of all pesticides at levels significantly above (189.84 ppb) the European Union preconized limits (<0.5 ppb). Using the mean pesticide concentration in water (ppb), the exposed population for each municipality, and the benchmark cancer risk for pesticides, we estimated the minimum number of cancer cases attributable to pesticide-contaminated drinking water during the period (total of 542 cases). More than 80% were attributed to mancozeb-ETU and diuron. Glyphosate-AMPA and diuron-attributable cases strongly correlated with the total cancer cases in the same period (R = 0.8117 and 0.8138, respectively) as well as with breast cancer cases (R = 0.7695 and 0.7551, respectively). Water contamination was significantly correlated with the sum of the estimated cancer cases for all 11 pesticides detected in each city (R = 0.58 and p < 0.0001). These findings reveal extensive contamination of drinking water in the state of Paraná and suggest that contamination may increase the risk of cancer in this region.

Estimating the early impact of vaccination against COVID-19 on deaths among elderly people in Brazil: Analyses of routinely-collected data on vaccine coverage and mortality.

Background: Vaccination against COVID-19 in Brazil started in January 2021, with health workers and the elderly as the priority groups. We assessed whether there was an impact of vaccinations on the mortality of elderly individuals in a context of wide transmission of the SARS-CoV-2 gamma (P.1) variant. Methods: By May 15, 2021, 238,414 COVID-19 deaths had been reported to the Brazilian Mortality Information System. Denominators for mortality rates were calculated by correcting population estimates for all-cause deaths reported in 2020. Proportionate mortality at ages 70-79 and 80+ years relative to deaths at all ages were calculated for deaths due to COVID-19 and to other causes, as were COVID-19 mortality rate ratios relative to individuals aged 0-69 years. Vaccine coverage data were obtained from the Ministry of Health. All results were tabulated by epidemiological weeks 1-19, 2021. Findings: The proportion of all COVID-19 deaths at ages 80+ years was over 25% in weeks 1-6 and declined rapidly to 12.4% in week 19, whereas proportionate COVID-19 mortality for individuals aged 70-79 years started to decline by week 15. Trends in proportionate mortality due to other causes remained stable. Mortality rates were over 13 times higher in the 80+ years age group compared to that of 0-69 year olds up to week 6, and declined to 5.0 times in week 19. Vaccination coverage (first dose) of 90% was reached by week 9 for individuals aged 80+ years and by week 13 for those aged 70-79 years. Coronavac accounted for 65.4% and AstraZeneca for 29.8% of all doses administered in weeks 1-4, compared to 36.5% and 53.3% in weeks 15-19, respectively. Interpretation: Rapid scaling up of vaccination coverage among elderly Brazilians was associated with important declines in relative mortality compared to younger individuals, in a setting where the gamma variant predominates. Had mortality rates among the elderly remained proportionate to what was observed up to week 6, an estimated additional 43,802 COVID-related deaths would have been expected up to week 19. Funding: CGV and AJDB are funded by the Todos pela Saúde (São Paulo, Brazil) initiative.

Reduction in life expectancy in Brazil after COVID-19.

Brazil has been heavily affected by coronavirus disease 2019 (COVID-19). In this study, we used data on reported total deaths in 2020 and in January-April 2021 to measure and compare the death toll across states. We estimate a decline in 2020 life expectancy at birth (e0) of 1.3 years, a mortality level not seen since 2014. The reduction in life expectancy at age 65 (e65) in 2020 was 0.9 years, setting Brazil back to 2012 levels. The decline was larger for males, widening by 9.1% the female-male gap in e0. Among states, Amazonas lost 60.4% of the improvements in e0 since 2000. In the first 4 months of 2021, COVID-19 deaths represented 107% of the total 2020 figures. Assuming that death rates would have been equal to 2019 all-cause rates in the absence of COVID-19, COVID-19 deaths in 2021 have already reduced e0 in 2021 by 1.8 years, which is slightly larger than the reduction estimated for 2020 under similar assumptions.

Characteristics, outcomes and risk factors for mortality of 522 167 patients hospitalised with COVID-19 in Brazil: a retrospective cohort study.

OBJECTIVE: To provide a comprehensive description of demographic, clinical and radiographic characteristics; treatment and case outcomes; and risk factors associated with in-hospital death of patients hospitalised with COVID-19 in Brazil. DESIGN: Retrospective cohort study of hospitalised patients diagnosed with COVID-19. SETTING: Data from all hospitals across Brazil. PARTICIPANTS: 522 167 hospitalised patients in Brazil by 14 December 2020 with severe acute respiratory illness, and a confirmed diagnosis for COVID-19. PRIMARY AND SECONDARY OUTCOME MEASURES: Prevalence of symptoms and comorbidities was compared by clinical outcomes and intensive care unit (ICU) admission status. Survival was assessed using Kaplan Meier survival estimates. Risk factors associated with in-hospital death were evaluated with multivariable Cox proportional hazards regression. RESULTS: Of the 522 167 patients included in this study, 56.7% were discharged, 0.002% died of other causes, 30.7% died of causes associated with COVID-19 and 10.2% remained hospitalised. The median age of patients was 61 years (IQR, 47-73), and of non-survivors 71 years (IQR, 60-80); 292 570 patients (56.0%) were men. At least one comorbidity was present in 64.5% of patients and in 76.8% of non-survivors. From illness onset, the median times to hospital and ICU admission were 6 days (IQR, 3-9) and 7 days (IQR, 3-10), respectively; 15 days (IQR, 9-24) to death and 15 days (IQR, 11-20) to hospital discharge. Risk factors for in-hospital death included old age, Black/Brown ethnoracial self-classification, ICU admission, being male, living in the North and Northeast regions and various comorbidities. Age had the highest HRs of 5.51 (95% CI: 4.91 to 6.18) for patients≥80, compared with those ≤20. CONCLUSIONS: Characteristics of patients and risk factors for in-hospital mortality highlight inequities of COVID-19 outcomes in Brazil. As the pandemic continues to unfold, targeted policies that address those inequities are needed to mitigate the unequal burden of COVID-19.

Spatiotemporal pattern of COVID-19 spread in Brazil.

Brazil has been severely hit by COVID-19, with rapid spatial spread of both cases and deaths. We used daily data on reported cases and deaths to understand, measure, and compare the spatiotemporal pattern of the spread across municipalities. Indicators of clustering, trajectories, speed, and intensity of the movement of COVID-19 to interior areas, combined with indices of policy measures, show that although no single narrative explains the diversity in the spread, an overall failure of implementing prompt, coordinated, and equitable responses in a context of stark local inequalities fueled disease spread. This resulted in high and unequal infection and mortality burdens. With a current surge in cases and deaths and several variants of concern in circulation, failure to mitigate the spread could further aggravate the burden.

Three-quarters attack rate of SARS-CoV-2 in the Brazilian Amazon during a largely unmitigated epidemic.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread rapidly in Manaus, the capital of Amazonas state in northern Brazil. The attack rate there is an estimate of the final size of the largely unmitigated epidemic that occurred in Manaus. We use a convenience sample of blood donors to show that by June 2020, 1 month after the epidemic peak in Manaus, 44% of the population had detectable immunoglobulin G (IgG) antibodies. Correcting for cases without a detectable antibody response and for antibody waning, we estimate a 66% attack rate in June, rising to 76% in October. This is higher than in São Paulo, in southeastern Brazil, where the estimated attack rate in October was 29%. These results confirm that when poorly controlled, COVID-19 can infect a large proportion of the population, causing high mortality.